Computer Vision-Based Monitoring of Bridge Structural Vibration During Incremental Launching Construction

Abstract

Conducting vibration monitoring during bridge construction is of significance for ensuring the safety of personnel and property and achieving safety risk management and controlling. However, current bridge vibration monitoring faces numerous challenges, including a large number of measurement points, significant frequency differences, vast structural scales, lack of fixed reference points, and difficulties in temporary deployment. This paper proposes a method for bridge structural vibration monitoring based on computer vision. The method utilizes high-definition cameras to capture dynamic images of bridges and incorporates advanced image processing algorithms to automatically identify and track the vibration characteristics of bridge structures, achieving low energy consumption, low cost, and high efficiency in monitoring. For developing this method, experiments were first conducted in an indoor environment using preset templates, where the amplitude error was within 0.5% and the frequency error was within 0.2%, verifying the feasibility and accuracy of the method. Subsequently, the size of the templates was altered, and the experimental results for five different template sizes were compared. The frequency errors were all within 0.2%, and the amplitude errors were all within 0.5%, with minimal differences, demonstrating the adaptability of the method. Subsequently, under the same indoor conditions, monitoring is conducted using the feature-based template matching method and cross-correlation-based method, respectively. The largest amplitude errors measured by the two methods were 5.59% and 14.39%, respectively, while the frequency errors were 1.82% and 1.02%, respectively. Finally, the method was applied to monitor the displacement of the piers during the jacking construction process of the Yongning Bridge.